All Outputs (7)

The taxonomy of tail risk (2024)
Journal Article
Stoja, E., Polanski, A., & Nguyen, L. H. (2024). The taxonomy of tail risk. Journal of Financial Research, https://doi.org/10.1111/jfir.12423

We use tail events at different levels of severity to define an asset's tail risk and to decompose the latter into a systematic and an idiosyncratic component. The systematic component captures an asset's tendency to experience joint tail losses with... Read More about The taxonomy of tail risk.

Does systematic tail risk matter? (2022)
Journal Article
Stoja, E., Polanski, A., Nguyen, L. H., & Pereverzin, A. (2023). Does systematic tail risk matter?. Journal of International Financial Markets, Institutions and Money, 82, Article 101698. https://doi.org/10.1016/j.intfin.2022.101698

Systematic tail risk is considered an important determinant of expected returns on risky assets. We examine its impact from two perspectives in a unified framework which originates from a simple asset pricing model. From the first perspective, system... Read More about Does systematic tail risk matter?.

International tail risk connectedness: Network and determinants (2021)
Journal Article
Nguyen, L. H., & Lambe, B. J. (2021). International tail risk connectedness: Network and determinants. Journal of International Financial Markets, Institutions and Money, 72, Article 101332. https://doi.org/10.1016/j.intfin.2021.101332

We construct a complete network of directional tail risk connectedness for 32 countries within a Least Absolute Shrinkage and Selection Operator (LASSO) Quantile Regression framework. In addition to highlighting the network's essential features, incl... Read More about International tail risk connectedness: Network and determinants.

Tail risk connectedness between US industries (2020)
Journal Article
Nguyen, L. H., Nguyen, L. X. D., & Tan, L. (2021). Tail risk connectedness between US industries. International Journal of Finance and Economics, 26(3), 3624-3650. https://doi.org/10.1002/ijfe.1979

We use the Least Absolute Shrinkage and Selection Operator (LASSO) quantile regression technique to construct and analyse the complete tail risk connectedness network of the whole US industry system. We also investigate the empirical relationship bet... Read More about Tail risk connectedness between US industries.

Investigating tail-risk dependence in the cryptocurrency markets: A LASSO quantile regression approach (2020)
Journal Article
Nguyen, L. H., Chevapatrakul, T., & Yao, K. (2020). Investigating tail-risk dependence in the cryptocurrency markets: A LASSO quantile regression approach. Journal of Empirical Finance, 58, 333-355. https://doi.org/10.1016/j.jempfin.2020.06.006

© 2020 Elsevier B.V. We construct the complete network of tail risk spillovers among major cryptocurrencies using the Least Absolute Shrinkage and Selection Operator (LASSO) quantile regression. We capture important features of the network, including... Read More about Investigating tail-risk dependence in the cryptocurrency markets: A LASSO quantile regression approach.

Extreme downside risk and market turbulence (2019)
Journal Article
Harris, R. D. F., Nguyen, L. H., & Stoja, E. (2019). Extreme downside risk and market turbulence. Quantitative Finance, 19(11), 1875-1892. https://doi.org/10.1080/14697688.2019.1614652

We investigate the dynamics of the relationship between returns and extreme downside risk in different states of the market by combining the framework of Bali, Demirtas, and Levy (2009) with a Markov switching mechanism. We show that the risk-return... Read More about Extreme downside risk and market turbulence.

Systematic Extreme Downside Risk (2019)
Journal Article
Harris, R. D. F., Nguyen, L. H., & Stoja, E. (2019). Systematic Extreme Downside Risk. Journal of International Financial Markets, Institutions and Money, 61, 128-142. https://doi.org/10.1016/j.intfin.2019.02.007

We propose new systematic tail risk measures constructed using two different approaches. The first is a non-parametric measure that captures the tendency of a stock to crash at the same time as the market, while the second is based on the sensitivity... Read More about Systematic Extreme Downside Risk.